Table 5 Comparisons of secondary renal pathological patterns predicted by the decision tree models on the basis of predicted probability of R2* data
Case Number | Pathological Diagnosis | Predicted Primary Class (percentage/number, %/n) | Decision Tree Model Result | Predicted Secondary Class (percentage/number, %/n) | Decision Tree Model Result | ||
|---|---|---|---|---|---|---|---|
III Type | IV Type | Homogeneity | Heterogeneity | ||||
Case 1 | IV-G (A/C) + V | 25% (74) | 75% (226) | IV | 17% (50) | 83% (250) | IV-G (A/C) + V |
Case 2 | IV-G (A/C) + V | 42% (125) | 58% (175) | IV | 5% (16) | 95% (284) | IV-G (A/C) + V |
Case 3 | IV-G (A/C) | 40% (119) | 60% (181) | IV | 35% (104) | 65% (196) | IV-G (A/C) + V |
Case 4 | IV-G (A/C) + V | 34% (103) | 66% (197) | IV | 30% (89) | 70% (211) | IV-G (A/C) + V |
Case 5 | III-(A/C) + V | 55% (166) | 45% (137) | III | 20% (61) | 80% (239) | III-(A/C) + V |
Case 6 | III-(A/C) + V | 60% (180) | 40% (120) | III | 6% (19) | 94% (281) | III-(A/C) + V |
Case 7 | III-(A/C) + V | 74% (221) | 26% (79) | III | 13% (39) | 87% (261) | III-(A/C) + V |
Case 8 | III-(A/C) | 73% (218) | 27% (82) | III | 60% (179) | 40% (121) | III-(A/C) |
Case 9 | III-(A/C) | 58% (173) | 42% (127) | III | 93% (280) | 7% (20) | III-(A/C) |
Case 10 | IV-G (A/C) | 23% (70) | 76% (230) | IV | 64% (192) | 36% (108) | IV-G (A/C) |
Case 11 | IV-G (A/C) | 22% (67) | 78% (238) | IV | 93% (279) | 7% (21) | IV-G (A/C) |
Case 12 | IV-G (A/C) + V | 11% (34) | 89% (266) | IV | 19% (58) | 81% (242) | IV-G (A/C) + V |